At Databricks, we are passionate about enabling data teams to solve the world's
toughest problems - from making the next mode of transportation a reality to
accelerating the development of medical breakthroughs. We do this by building
and running the world's best data and AI infrastructure platform so our
customers can use deep data insights to improve their business.
Ingesting data into the Lakehouse is a strategic area of investment for
Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is
looking to solve this problem by providing ready-to-use, point-and-click
connectors for a wide variety of sources, including enterprise applications
(like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL
Server), cloud storage, message queues, and local files.
In addition to being an key part of Lakeflow and Data Engineering, Connect
is also a key platform capability. Every surface in Databricks (Dashboards,
Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role
will need to work closely with other products to embed Connect into these
surfaces.
We are looking for engineers with experience in core Database internals to join
our Lakeflow Connect team. A key part of Connect is to extract data from OLTP
systems while imposing minimal load on production systems. To do this
efficiently we are building systems that use techniques such as incremental data
capture, log parsing, etc. We are looking for engineers who continue to be hands
on and are looking to make a large impact on an important problem for the
company.
The Impact you will have:
* Solve real business needs at large scale by applying your software
engineering.
* Deliver a highly scalable, available, and fault-tolerant engine processing
hundreds of TB of data daily across thousands of customers
* Low level systems debugging, performance measurement & optimization on large
production clusters.
* Build architecture design, influence product roadm